• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.125-133
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• 2017

Recently, as the programming education has become essential in school, discussion of how to teach programming has been important. This study performed a meta-analysis of the effect size depending on the teaching and learning method for the programming education. 78 research data selected from 45 papers were analyzed from cognitive and affective aspects according to dependent variables. The analysis from the cognitive aspect showed that there was no statistically significant difference in the effect size depending on whether or not the teaching and learning method was specified in the research paper. Meta-analysis of the research data where the teaching and learning method was designated displayed significances in CPS, PBL and Storytelling. Unlike the cognitive aspect, the analysis from the affective aspect showed that the effect size of the research data without the specified teaching and learning method was larger than those with specified teaching and learning method with a statistical significance. Meta-analysis of the data according to the teaching and learning method displayed no statistical significance. Based upon these research results, this study suggested implications for the effective programming education.

• Journal of KIISE:Software and Applications
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• v.36 no.6
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• pp.498-507
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• 2009

There has been insufficient studies on the effect of programming language learning on logical thinking ability. Each study result on the improvement degree and items of logical thinking ability is different according to the object of the study, its method, and the learning subject, which makes the generalization process difficult. Moreover, the necessity of programming language learning seems not proved, because it is not apparent whether the improvement of logical thinking ability is due to the advancement of knowledge or programming language learning. In this study, we instructed educational programming languages to elementary students in 6th grade for 7 hours, investigated its effect on logical-thinking ability by the meta-cognition level, and compared the result with that of computer skill learning. As a result, for Dolittle, LOGO, and Powerpoint learning groups, the logical-thinking ability of high meta-cognition level students has increased with significance, but that of low meta-cognition level students has significantly increased for Dolittle and LOGO groups only. However, regardless of meta-cognition levels, there was no significant difference of logical-thinking ability between all three groups.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• Journal of The Korean Association of Information Education
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• v.12 no.4
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• pp.375-384
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• 2008

Computer programming has educational effect on improving high-level thinking abilities. However, students initially have to spend too much effort in learning the basic grammar and the usage model of programming languages, which negatively affects their eagerness in learning. To remedy this problem, we propose to apply the Scratch to a Game Developing Programming Class; Scratch is an easy-to-learn and intuitive Educational Programming Language (EPL) that helps improving the Meta-cognition and Self-efficacy of middle school students. Also we used the Demonstration-Practice instruction model with self-questioning method for activating the Meta-cognition. In summary, a game developing programming class using Scratch was shown to significantly improve the Meta-cognition of middle school students. However it was shown to insignificantly improve the Self-efficacy of girl students group.

• Journal of the Korea Society of Computer and Information
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• v.23 no.6
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• pp.81-89
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• 2018

In this paper, we propose to investigate the existing EPL education related studies and to collect the total effect size for the improvement of high-level thinking through meta-analysis and to confirm the effect size according to various variables. So, we have objectively identified and generalized the practical effects of EPL education on the various elements of high-level thinking and high-level thinking. The results of the meta-analysis showed that 1) EPL is a teaching-learning tool that greatly improves students' high-level thinking. 2) Education based EPL has greatly contributed to the enhancement of creative thinking and logical thinking among high-level thinking. 3) Kodu, App Inventor, Scratch, and Dolittle was confirmed that the effect on the improvement of high-level thinking was great.

• Journal of The Korean Association of Information Education
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• v.18 no.3
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• pp.413-422
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• 2014

The positive impacts of robotics education and programming education on learners are similar. However, robotics education differs from programming education because it includes purchasing and building robots that cause financial and cognitive load of learners. Due to these differences, two kinds of education may not possess equal efficacies for all schools or all learning objectives. To verify this hypothesis, we conducted meta-analysis of studies on robotics education published in South Korea to estimate the effect sizes and compare it to that of programming education. The difference between the average effect sizes of robotics education and of programming education was significant, as the former was 0.4060 and the latter 0.6664. The average effect size of programming education was significantly larger than that of robotics education for primary school students. Middle school students achieved the highest results in both robotics education and programming education. Also, robotics education became more effective than programming education as students were older. Analysis on objectives showed that programming education uniformly affected all areas, whereas robotics education had more impact on affective domain than cognitive domain. Robot construction had the largest effect size, followed by robot construction and programming, robot programming, and robot utilization. Programming education has larger positive impacts on students overall compared to robotics education. Robotics education is more effective to upperclassmen than programming education, and improves affective domain of students. Also, robotics education shows higher efficacy when combined with various subjects.

• The Journal of Korean Association of Computer Education
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• v.19 no.2
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• pp.21-29
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• 2016

The introduction of educational programming language has changed programming learning environment to learn programming through various learning activities. We need to analyze how effective these learning activities could be in programming learning. We performed a meta analysis of the programming learning effects according to 8 types of learning activities. The 44 studies were collected from 1993 to 2015 for the meta analysis. The study data of 77 were extracted among 44 studies through several steps. The major results were as follows. The effect size of cognitive domain was shown to be mid-level with .595 and the effect size of affective domain was shown to be mid-level with .594. We analysed according to learning activities. The effect size were no significant difference between learning activities in the cognitive domain. But simulation, animation and mathematical activities was shown to be more consistent results and mid-level effect size. Although the effect size were no significant difference, the homogeneity was shown to be high in the affective domain. The implications were suggested from research findings. First, it is desirable that learners learn programming according to various learning activity themes. Second, instructors should pay attention to simulation, animation and mathmatics activities. Third, researchers need research to find another factors for effective learning.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.317-324
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• 2014

In this paper, we investigate the effects of programming education using educational programming languages. We select 70 papers which contain 101 individual experimental studies we can estimate the effect size from. The average effect size of the studies is .641, which means that programming education has modest effects on the learners. The average effect size of the learners' cognitive and affective domains are 0.632 and 0.666, respectively. The average effect size by the controlled variables such as school level, experimental periods, and programming languages have no statistically significant difference. The results of our study show that the experimental group receiving programming education, can be expected perform about 23.9% better compared to the control group having received no programming education.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.800-807
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• 2008

We introduce some well-known approaches to formalization and automatization of the meta-theory of a programming language with binders. They represent the trends in POPLmark Challenge. We demonstrate some characteristics of each approach by showing how to formalize some basic notations and concepts of Lambda-calculus using the proof assistant Coq.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.57.3-57
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• 2002

1. Introduction 2. General flux balance model 3. MetaFluxNet 3.1 Overview of MetaFluxNet 3.2 Project file format 3.3 Construction of metabolite reaction model 3.4 Metabolic flux analysis using linear programming 3.5 Visualization of MFA results 4. Conclusion and plan 5. Acknowledgement. References.